EMERGING BIOMARKERS FOR CARDIOVASCULAR DISEASE PROGNOSIS IN DIABETIC PATIENTS: A NARRATIVE REVIEW.

Abstract

Cardiovascular disease (CVD) is the leading cause of morbidity and death among patients with diabetes, presenting a significant global health challenge. Traditional biomarkers have limitations in accurately predicting CVD risk in this population, highlighting the need for novel biomarkers that offer improved precision and specificity. The review aims to critically evaluate current research on novel biomarkers for CVD prognosis in diabetic patients, synthesizing evidence on genetic, proteomic, metabolic, and inflammatory markers. An organized literature search was managed across multiple electronic databases, yielding a comprehensive selection of studies investigating biomarkers associated with CVD prognosis in diabetic individuals. Findings reveal emerging biomarkers with potential predictive value, such as genetic variants, inflammatory proteins, and metabolic metabolites. These biomarkers offer insights into the pathophysiological mechanisms underlying CVD in diabetes and show promise for improving risk stratification and early detection. The integration of novel biomarkers into clinical practice could revolutionize the management of CVD in diabetic patients by enabling personalized risk assessment and targeted interventions. However, challenges such as validation, standardization, and integration into existing clinical workflows need to be addressed. Future research should focus on longitudinal studies to elucidate the dynamic nature of biomarkers and leverage technological advancements to enhance their predictive value. The identification and validation of novel biomarkers hold potential implications for clinical policy and development. Incorporating these biomarkers into risk assessment algorithms and treatment guidelines could optimize patient outcomes and contribute to more efficient healthcare resource allocation. However, education and training for healthcare providers on biomarker interpretation and clinical implications are essential for successful implementation.